Fingerprint image edge detection based on fractal Brownian motion

Aiming at the existing questions in the preprocessing step of fingerprint image, an improved edge detection algorithm is presented based on the concept of fractal Brownian motion model in this paper. Due to the fact that the structure of fingerprint is typically self-similar, which satisfies the model of fractional Brownian random field except edges, so it can be used as the principle of detection. By selecting those pixels that fractal parameters are in a certain range, the fingerprint edges can be detected. The results of experiment have shown that this improved algorithm obtain much more edge details than most traditional methods do and reflect the edge information of original image much better. At the same time, this algorithm reduces the computation complexity greatly and enhances the speed of edge detection.